Presentation at the HLEG thematic workshop on Measuring Inequalities of Income and Wealth, 15-16 September 2015, Berlin, Germany, http://oe.cd/hleg-workshop-inequalities-income-and-wealth

1. Combined use of survey and
administrative data in EU-SILC
(EU Statistics on Income and Living Conditions)
Veli-Matti Törmälehto
HLEG Workshop on Measuring Inequalities of Income and Wealth
Berlin 15-16 September 2015

2. Outline
－ EU-SILC as a framework for surveys on income and living
conditions in Europe
－ ”Register” and ”survey” countries in EU-SILC
－ Preconditions, benefits and disadvantages of using register data
－ Comparisons of inequality indicators based on interview and
register income data
－ Concluding remarks
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3. EU Statistics on Income and Living
Conditions
EU-SILC is “the reference source for comparative statistics on income
distribution and social inclusion in the European Union (EU). “’
The EU legal framework and implementation regulations, guidelines and
recommendations specify:
－ the list of target variables to be transmitted to Eurostat
－ common definitions, concepts and units, classifications
－ minimum effective sample sizes, transmission deadlines, quality reporting
Flexibility of implementation: no standard questionnaire, different sampling
designs, survey modes, data sources, calibration models…
 Annual ex-ante output harmonised sample surveys from more than 30
European countries: micro data, multidimensional contents, detailed income data
one of the core areas, main income concept disposable cash and near cash income
(Canberra group definition)
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4. EU-SILC framework and registers
The EU legal framework (from 2003) takes the use of registers in
surveys explicitly into account:
－ 1) as a possible data source alongside interview data
－ 2) with the so-called ”selected respondent” design and variables
Originally, to accomodate the needs of the Nordic countries
Recently: expansion in the number of EU-SILC countries using
income data from registers
 Three EU-SILC country groups:
1. ”Register countries using the selected respondent design”,
2. ”Register income countries”
3. ”Survey” countries
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5. ”Register” and ”survey” countries in EU-
SILC (income data, EU-SILC 2013)
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”Old register countries”: Nordic + NL + SI:
extensive use of registers (income, other
domains), sampling of individuals , selected
respondent design (SR variables, cohort
panels,only one adult interviewed), mainly
telephone interviews
”New register income countries”:
France, Switzerland, Austria: income data mostly
from registers; Estonia, Latvia, Lithuania, Italy,
Spain, Ireland: income partly from registers and/or
mixed methods
Have not adapted basic designs (interview all
adults 16+, classical panels)
”Survey countries”: income data collected in
interviews

6. Preconditions for using register data in EU-
SILC
1. No legal & actual barriers to obtain and use register data in SILC
－ existing national legislation must not prevent obtaining, linking and disseminating register
micro data to Eurostat and to researchers
－ adaptation of national laws may be the first required step (e.g. Netherlands, Austria)
－ timeliness a serious constraint: late availability of registers vs. Eurostat transmission deadline
－ confidentiality a more serious concern with register data
2. Consent from the survey respondents (explicit request or ”soft” informing)
－ far from obvious in certain countries (e.g. UK), not an issue in most register countries
3. Common identifiers for record linkage
－ Many SILC register countries link multiple register sources to the sample (at least social
security and tax data) – not just ”tax records”
－ Most SILC register countries can use personal identification numbers or otherwise exactly
match the data (exact matching instead of probabilistic linkage)
－ Facilitated by register of households, preloading to electronic questionnaire, panel component
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7. Registers and survey errors: general issues
The combined use of survey and register data expands the
traditional survey error sources (see Zhang, 2012):
– 1st phase errors, in single sources (survey or register): representation & measurement
– 2nd phase errors, related to linking of various data sources: different units (persons,
tax units), failed linkages, identification errors
But: errors in any single source also can be compensated with data from
other sources (interviews vs. registers / two or more income registers)
– Registers may have partial coverage of recipients, regions, or types of
income, e.g .inter-household transfers, income subject to final withholding
tax, income from abroad; low quality of self-declared tax data: tax evasion,
self-employment income…
– Interviews have recall bias, proxy respondents, misunderstanding of concepts
 small amounts often forgotten (extensive vs. intensive margin), less
frequently paid less accurately measured, net vs. gross, misidentification of
benefits; also dependent on how detailed the questionnaire is
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8. EU Statistics on Income and Living
Conditions: some questions
Variation in errors in register data:
- within countries in different types of register data (self-declared vs.
third-party reported; e.g. pensions vs. self-employment or rental
income)
- between countries (e.g. extent of tax evasion)
Income questions usually cannot be completely eliminated from the
SILC questionnaire:
- supplementary items collected in interviews (e.g. inter-household
transfers), and/or
- income component collected from both registers and interviews (e.g.
self-employment incomes in Italy), or from either depending on
household sub-group (e.g. Basque province in Spain)
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9. Flexiblity of data sources vs. comparability
By necessity, some EU-SILC countries will continue relying on
interview-based data on incomes, and some will take data mostly
from registers, so the split to at least two groups will remain
Flexible use of data sources reduces survey errors within countries,
but may introduce additional bias to cross-country comparisons
How does transition from interview income data to register income
data affect common inequality indicators?
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10. Early studies in the EU-SILC context
Interview Registers Interview Registers Change,
interview
Change,
registers
1995 1995 1999 1999 1995-
1999
1995-
1999
Gini (%) 23.8 22.6 26.5 25.1 2.7 (11 %) 2.5 (11 %)
Poverty
(50 %)
7.1 4.5 8.4 5.9 1.3 (18 %) 1.4 (31 %)
Source: Nordberg et al. (2004): ”Measurement Error of Survey and Register Income”
Register and interview income data: estimates of inequality and poverty in
Finland: European Community Household Panels 1995 and 1999
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Finland 1995 and 1999: register-based data signals lower inequality and
substantially lower income poverty rates
On average, interview incomes 5 % lower than register incomes;
differences quite stable over time, trend not affected

11. Recent evidence based on EU-SILC data
Examination of three countries that have started using register
income data recently, and have indicators flagged as breaks in time-
series in Eurostat database:
1) Austria: overlapping measurement 2007-2011*, break in series 2007,
validation study, circa 87 % of total income now comes from registers, mostly via
substitution, capital & SE income from interviews, also changes in calibration
2) Spain: overlapping measurement 2008-2011, break in series 2008, validation
study, ”mixed method” of combining registers and interviews
3) France: no overlapping measurement, break in series 2007, substitution &
supplementary interview data on self-employment and types of income
* years refer to income reference years (survey year - 1)
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12. EU-SILC Gini-coefficients, Austria and Spain,
interview- vs. register-based income data
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26.1 26.3
27.7
27.4
33
35
32.9
34.2
24.0
25.0
26.0
27.0
28.0
29.0
30.0
31.0
32.0
33.0
34.0
35.0
36.0
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Gini,%
Income reference year
Austria - interviews Austria - registers
Spain - interviews Spain registers
Sources: J-M Méndez Martin (2015), Statistics Austria (2014)

13. Gini coefficient in France according to
Eurostat, OECD, INSEE
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27.7
26.6
29.8
28.1
26
26.5
27
27.5
28
28.5
29
29.5
30
30.5
31
2004 2005 2006 2007 2008 2009 2010 2011 2012
Gini,%
Eurostat (modified OECD, break in 2007 due to register income data)
OECD (square root scale, best national source)
Insee, enquête Revenus fiscaux et sociaux (ERFS, modified OECD)

14. EU-SILC income shares in France
(break in 2007/EU-SILC 2008)
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5.7
13.3
16.0
21.9
25.2
3.8
23.6
22.4
0.0
5.0
10.0
15.0
20.0
25.0
30.0
2004 2005 2006 2007 2008 2009 2010 2011 2012
%ofequivalentdisposableincome
Income reference year
Top 1 % Top 5 % Top 10 % Bottom 10 % Bottom 40 %
Source: Eurostat (table ilcdi01). Year refers to income reference year.

15. At-risk-of-poverty rates (60 % of median)
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12.4
15.2
20.1
22.2
20.4
20.8
12.5
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Atriskofpovertyrate,60%ofmedian
Income reference year
Austria - interviews Austria - registers
Spain - interviews Spain -registers
France
Sources: J-M Méndez Martin (2015), Statistics Austria (2014), Eurostat database

16. Headcount income poverty rates (30-70 % of median),
Austria and Spain 2011 (EU-SILC 2012)
16 15 September 2015 Veli-Matti Törmälehto
Source: Own elaboration from EU-SILC UDB versions August 2014 (interviews) and March 2015 (Registers)
0.0
5.0
10.0
15.0
20.0
25.0
30.0
30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
%ofpersons
Equivalent disposable income,
% of median
Austria - interviews Austria - registers
Spain - interviews Spain - registers

17. Change in median income by deciles,
register vs. interview incomes, 2010 (EU-SILC 2011)
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57%
15%
-2.1 %
2.0 %
-10%
0%
10%
20%
30%
40%
50%
60%
70%
I II III IV V VI VII VIII IX X All
Spain 2010 (EU-SILC 2011) Austria 2010 (EU-SILC 2011)
Source: Own elaboration from EU-SILC UDB versions August 2014 (interviews) and March 2015 (Registers)

18. Median income by deciles, euro
register and interview incomes, 2010 (EU-SILC 2011)
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0
2500
5000
7500
10000
12500
15000
17500
20000
22500
25000
27500
30000
32500
35000
37500
40000
42500
45000
47500
50000
I II III IV V VI VII VIII IX X
EquivalentDPI,euro
Income decile
Spain -registers Austria - registers
Spain - interviews Austria - interviews
Source: Own elaboration from EU-SILC UDB versions August 2014 (interviews) and March 2015 (Registers)

19. Summary of selected results on the effects
on indicators
－ In Austria: higher inequality and poverty, average income level almost
unchanged using register data on wages and salaries and transfers compared to
to interview data (Statistics Austria 2014)
－ In France: no direct overlapping measurement, but indicators & research
suggest transition to register data implies higher inequality, stable cross-sectional
poverty measures and fatter right tail (see Burricand, 2013)
－ In Spain: lower income inequality and poverty, much higher average income level
using both register and interview data compared to using just interview data
(Mendez 2015)
－ In Italy: lower income inequality (Gini 33.0  31.3) and poverty (21.4 %  19.6 %)
using both interview and register data on wages and salaries, pensions and self-
employment income (+microsimulation for taxes) (Consolini and Donatiello, 2013)
－ In Finland (1990s ECHP): lower income inequality and poverty, higher average
income level from registers compared to using interview data (Nordberg et al.
2004)
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20. Top 5 % income shares: World Top Incomes
Database & EU-SILC, selected countries 2009
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20.7
18 18
19.1
21.4 21.4
22.9 23.2
17.9
16.9
16.1
19.1
20.2 20.1 19.7
21.3
0
5
10
15
20
25
Finland Norway Sweden Netherlands France Spain Switzerland Italy
Top5%incomeshare,%
WTID (adults, tax data)
Adjusted SILC- estimate, pre-tax personal incomes (HH-level incomes equally divided), 16+ persons
Original SILC-estimate (2009 incomes), equivalent household DPI, person weighted
WTID for Finland is an estimate based on EU-SILC
sample – taxable income of persons 15+

21. Coherence: EU-SILC & ”best national
sources”
Register income data can be used in other statistics, and coupled with
calibration, coherence of different national sources can be very good (incl.
HBS & National Accounts)
However, in the Nordic countries, main national sources on income
distribution are now entirely register-based household income statistics for
the whole population instead of sample surveys (Denmark, Norway, Finland,
Sweden)
 Requires a register of households for statistical purposes (”dwelling units”), near complete
register income data; there is no unit & item non-response, highly disaggregated data and
panels, usually include realized capital gains
Coherence is still an issue; differences between ”best national sources” and
EU-SILC & relevance of EU-SILC at national level in register countries?
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Gini (%), 2010 EU-SILC OECD NSI
(excl. capital gains)
NSI
(incl. capital gains)
Sweden 24.4 26.9 26.5 29.7
Finland 25.8 26.4 27.2 28.2

22. Concluding remarks
－ To minimize measurement errors of income in sample surveys, the best way is to
combine register and interview-based data: both sources have shortcomings
－ The use of register-based income data has expanded rapidly in EU-SILC in recent
years, but the division to ”survey” and ”register” countries is not going away
－ The evidence from validation studies on the distributional impact of using register
vs. interview data is inconclusive (or even confusing)
－ Levels of inequality, poverty and average income may change markedly in some
cases, but in different directions; trends over time seem less affected
－ Aside from measurement errors, the observed distributional impact may depend
on other changes in the survey production process, e.g. reweighting; income
definition remains important (coverage, treatment of negatives…)
－ Use of registers affects the whole survey: shorter questionnaires  cheaper
modes of collection feasible (CATI, CAWI); less imputations but more data
processing; unit non-response analysis and survey weighting can be vastly
improved
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23. Concluding remarks
Key tradeoffs in EU-SILC related to the use of administrative data:
1. Accuracy vs. timeliness: timeliness is currently the first priority in
the ongoing revision of EU-SILC legal basis
– first statistics on inequality 12 or even 6 months after the income reference
period, nowcasting in register countries?
2. Comparability vs. flexibility of data sources: EU-SILC is likely to
have even more variation in data sources and survey modes in the
future
– from personal interviews to cheaper alternatives, mixed mode incl. web
– joint distribution of income, consumption and wealth: interviews, registers
statistical matching, estimation
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24. Thank you for your attention!
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